Staff Machine Learning Engineer
About The Position
Join EvenUp as a Staff Machine Learning Engineer and help set the technical direction for how machine learning powers Piai™, our proprietary claims-intelligence platform. This is a technical leadership role - you'll shape modeling strategy across a broad problem space, turning raw legal and medical data into production systems that improve outcomes for personal-injury clients. You'll partner closely with Product, Research, and Engineering leaders to set strategy, and you'll be a technical anchor for the broader ML team - setting standards, mentoring senior engineers, and driving decisions that shape both product outcomes and company growth.
Requirements
- 7+ years of hands-on ML engineering experience, with multiple models shipped and running in production.
- Deep expertise in ML and NLP, including LLMs, with a track record of solving hard modeling problems - not just applying existing recipes.
- High proficiency in Python and strong command of modern ML/NLP frameworks.
- Demonstrated ability to set technical strategy and drive execution in ambiguous, fast-moving environments.
- A track record of mentoring engineers and raising technical standards beyond your own output.
- Experience partnering directly with Product and Engineering leadership, not just executing their asks.
Nice To Haves
- PhD in Machine Learning, Computer Science, or a related quantitative field.
- Experience with document understanding, entity/relationship extraction, or structured extraction from unstructured text.
- Experience with LLM fine-tuning techniques (LoRA, QLoRA, RLHF/RLVR) or advanced prompt engineering.
- Experience in a high-growth startup environment.
Responsibilities
- Set technical strategy for a broad area of the ML roadmap, translating ambiguous business and research goals into scoped, production-ready systems.
- Tackle the hardest modeling problems in the org - complex reasoning, long-context and multi-document understanding, or other frontier challenges as they come up.
- Apply advanced ML techniques - fine-tuning, reinforcement learning, retrieval, or others - and know when a technique is the right tool versus over-engineering.
- Establish rigorous evaluation standards, reducing hallucinations, improving factual consistency, and defining what "good" looks like for a given system.
- Drive data excellence through hands-on analysis of training and evaluation data, managing noise, edge cases, and drift at scale.
- Provide technical leadership and mentorship across the ML team, raising the bar for experimentation, benchmarking, and engineering rigor.
- Act as the bridge between research and production - ensuring new techniques get integrated into shippable systems, not just proofs of concept.
- Partner cross-functionally with product, engineering, and legal subject-matter experts to set technical direction.
- Cost effectively scale practical machine learning systems in a hyper-growth environment, ensuring they remain grounded in real business and customer needs.
Benefits
- Choice of medical, dental, and vision insurance plans for you and your family.
- Additional insurance coverage options for life, accident, or critical illness.
- Flexible paid time off, sick leave, short-term and long-term disability.
- 10 US observed holidays, and Canadian statutory holidays by province.
- A home office stipend.
- 401(k) for US-based employees and RRSP for Canada-based employees.
- Paid parental leave.
- A local in-person meet-up program.
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What This Job Offers
Job Type
Full-time
Career Level
Senior
Education Level
Ph.D. or professional degree
